Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	20,313
2	New Jersey	19,370
3	Rhode Island	15,707
4	Massachusetts	15,645
5	District of Columbia	14,394
6	Connecticut	12,900
7	Louisiana	11,514
8	Delaware	11,275
9	Illinois	11,121
10	Maryland	10,982
11	Nebraska	9,484
12	Arizona	8,696
13	Iowa	8,679
14	Mississippi	8,237
15	South Dakota	7,323
16	Virginia	7,023
17	Michigan	6,925
18	Pennsylvania	6,891
19	Alabama	6,772
20	Indiana	6,651
21	Georgia	6,385
22	Utah	6,096
23	Minnesota	6,056
24	Arkansas	5,985
25	South Carolina	5,636
26	Tennessee	5,519
27	North Carolina	5,486
28	Colorado	5,463
29	New Mexico	5,337
30	Florida	5,308
31	California	5,097
32	Nevada	4,840
33	Texas	4,717
34	Wisconsin	4,539
35	Kansas	4,533
36	North Dakota	4,464
37	Washington	4,202
38	New Hampshire	4,146
39	Ohio	4,076
40	Kentucky	3,311
41	Missouri	3,271
42	Oklahoma	3,019
43	Idaho	2,724
44	Wyoming	2,291
45	Maine	2,283
46	Puerto Rico	2,153
47	Vermont	1,908
48	Oregon	1,795
49	West Virginia	1,503
50	Alaska	1,327
51	Montana	751
52	Hawaii	590

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Arizona	390
2	Mississippi	249
3	Louisiana	227
4	Arkansas	218
5	South Carolina	215
6	Florida	214
7	Texas	197
8	Alabama	187
9	Georgia	159
10	Utah	156
11	Nevada	144
12	California	141
13	Iowa	123
14	Tennessee	119
15	North Carolina	117
16	Idaho	112
17	Oklahoma	102
18	New Jersey	98
19	New Mexico	79
20	Kansas	72
21	Missouri	72
22	Wisconsin	71
23	Washington	68
24	Nebraska	67
25	Maryland	65
26	Illinois	61
27	Ohio	60
28	South Dakota	57
29	Virginia	57
30	Rhode Island	56
31	Wyoming	55
32	Delaware	54
33	Kentucky	53
34	Minnesota	53
35	Indiana	52
36	District of Columbia	47
37	Alaska	46
38	Colorado	44
39	Pennsylvania	40
40	Oregon	38
41	North Dakota	36
42	Michigan	33
43	New York	32
44	Puerto Rico	32
45	Massachusetts	30
46	Maine	24
47	West Virginia	22
48	Montana	21
49	Connecticut	19
50	New Hampshire	19
51	Vermont	14
52	Hawaii	7

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	1,674
2	New York	1,595
3	Connecticut	1,205
4	Massachusetts	1,155
5	Rhode Island	868
6	District of Columbia	769
7	Louisiana	680
8	Michigan	614
9	Illinois	554
10	Delaware	520
11	Maryland	517
12	Pennsylvania	515
13	Indiana	384
14	Mississippi	341
15	Colorado	289
16	New Hampshire	262
17	Minnesota	255
18	Georgia	254
19	Ohio	237
20	New Mexico	231
21	Iowa	222
22	Arizona	205
23	Virginia	196
24	Alabama	182
25	Washington	170
26	Missouri	163
27	Nevada	160
28	Florida	154
29	California	147
30	Nebraska	137
31	South Carolina	134
32	Wisconsin	131
33	Kentucky	127
34	North Carolina	124
35	North Dakota	114
36	South Dakota	98
37	Oklahoma	94
38	Kansas	90
39	Vermont	89
40	Tennessee	81
41	Texas	80
42	Arkansas	79
43	Maine	76
44	Utah	51
45	West Virginia	51
46	Idaho	50
47	Oregon	47
48	Puerto Rico	47
49	Wyoming	34
50	Montana	19
51	Alaska	13
52	Hawaii	12

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New Jersey	74
2	Delaware	24
3	Arizona	6
4	Rhode Island	5
5	Massachusetts	4
6	Mississippi	4
7	New Hampshire	4
8	Alabama	3
9	Connecticut	3
10	District of Columbia	3
11	Georgia	3
12	Illinois	3
13	Louisiana	3
14	Maryland	3
15	Pennsylvania	3
16	California	2
17	Florida	2
18	New Mexico	2
19	South Carolina	2
20	South Dakota	2
21	Virginia	2
22	Arkansas	1
23	Colorado	1
24	Indiana	1
25	Iowa	1
26	Kentucky	1
27	Michigan	1
28	Minnesota	1
29	Missouri	1
30	Nebraska	1
31	New York	1
32	North Carolina	1
33	North Dakota	1
34	Ohio	1
35	Tennessee	1
36	Texas	1
37	Washington	1
38	Wisconsin	1
39	Alaska	0
40	Hawaii	0
41	Idaho	0
42	Kansas	0
43	Maine	0
44	Montana	0
45	Nevada	0
46	Oklahoma	0
47	Oregon	0
48	Puerto Rico	0
49	Utah	0
50	Vermont	0
51	West Virginia	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	130,362	1	99
Lake	Tennessee	98,347	2	99
Dakota	Nebraska	87,936	3	99
Buena Vista	Iowa	85,474	4	99
Lincoln	Arkansas	79,545	5	99
Davidson	Tennessee	12,453	220	92
Richland	South Carolina	7,110	536	82
Orange	California	3,717	1078	65
York	South Carolina	3,370	1168	62
Pierce	Washington	2,993	1291	58

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Hancock	Georgia	3,784	1	99
Randolph	Georgia	3,688	2	99
Terrell	Georgia	3,165	3	99
Early	Georgia	3,042	4	99
Essex	New Jersey	2,517	5	99
Richland	South Carolina	192	672	78
Davidson	Tennessee	148	797	74
Pierce	Washington	107	977	68
Orange	California	96	1036	67
York	South Carolina	43	1490	52

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.